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

More documents

Recommendations

Info

J.L. Hernández-Stefanoni et al. 2010. Effects of landscape structure and stand age on species richness and biomass 642 configuration affects the structure and composition of plant communities depends on processes occurring at different spatial scales (Cushman and McGarigal, 2004). In order to assess the relationship between community attributes and landscape structure across different scales it is necessary to consider scale-dependent ecological processes (Bellier et al, 2007). Thus, the goal of this study was to relate plant species density and biomass with landscape structure, stand age and spatial variation of ecological structure at different spatial scales. 2. Methods 2.1 Study Area The study was conducted in a landscape mosaic of 22 x 16 km 2 in Yucatán, México. The climate is tropical, warm, with summer rain and a dry season from November to April. Mean annual temperature is ca 26ºC, and mean annual precipitation between 1000 and 1200 mm, concentrated between June and October. The landscape consists of Cenozoic limestone hills with moderate slope (10-25°) alternating with flat areas, and the elevation ranges from 60 to 160 m.a.s.l (Flores and Espejel 1994). The landscape is dominated by seasonally dry semideciduous tropical forests of different ages of abandonment after traditional slash-and-burn agriculture (Figure 1). 2.2 Remotely sensed data and imagery processing A Spot 5 satellite image acquired on January 2005 was geo-referenced to Universal Transverse Mercator Projection (WGS 84) and radiometrically corrected to minimize the effect of atmospheric scattering. A false color composite image was created from bands 2 (red), 3 (near infrared), and 4 (mid infrared). This composite image was used as a spatial reference framework for selecting suitable training sites. At least three training sites were selected for each of the following land-cover types: 1) 3-8 y-old secondary forest; 2) 9-15 y-old secondary forest; 3) >15 y-old secondary forest on flat areas; 4) >15 y-old secondary forest on hills; 5) agricultural fields; 6) urban areas and roads. The training areas and the false color image were used to perform a standard supervised classification of the Spot 5 bands using the maximum likelihood algorithm (Idrisi Kilimanjaro V14.1, 2004). The overall accuracy and Cohen’s Kappa statistic were used to assess the accuracy of the map (Campbell, 1987). 2.3 Calculation of landscape pattern metrics We selected the following metrics that have been found relevant in landscape studies (Mazerolle & Villard, 1999): patch density (PD), edge density (ED), mean area weighted shape index (SHAPE_AM), mean area weighted proximity index (PROX_AM), mean area weighted Euclidean nearest neighbor distance (ENN_AM) and total edge contrast index (TECI; see McGarigal et al. 2002 for a description of each metric). To calculate the proximity index, a search radius of 10 pixels (300 m) was used, which coincides with empirically derived evidence about the average size of a patch type. The weighted edge contrast between vegetation cover classes, required to compute the total edge contrast index, was calculated as the inverse of the Morisita-Horn similarity index between each pair of vegetation cover classes. 2.4 Species density and biomass data Field data were recorded from a hierarchical plant survey conducted during the rainy season of 2009. First, 23 landscapes of 1 km 2 were selected encompassing the whole range of forest fragmentation; within each landscape, 12 sample sites were located following a stratified random design considering each of the four secondary forest cover classes (276 sampling sites in total). Each sampling site consisted of two concentric circular plots: all woody plants > 5 cm 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.
J.L. Hernández-Stefanoni et al. 2010. Effects of landscape structure and stand age on species richness and biomass 643 in DBH (diameter at breast (1.3 m) height), hereafter referred to as adults, were sampled in a 200 m 2 plot; whereas 1-5 cm DBH woody plants, hereafter referred to as juveniles, were sampled in a nested 50 m 2 subplot. In each site, we identified all woody plants, and measured their diameter and height. The number of adults, juveniles and all woody plant species was computed. To calculate above-ground biomass, two equations were employed: one for individuals ≥ 10 cm in DBH (Cairns et al, 2003) and the other for individuals < 10 cm in DBH (Hughes et al, 2000). 2.5 Data analysis Multiple regression and variation partitioning methods (Bocard et al, 2004) were used to quantify the effects of landscape structure and spatial dependence on species density and biomass. First, a model using landscape structure and stand age variables was fit to the response variables using multiple regression. Then, a multiple regression model using spatial variables derived from a principal coordinate of neighbor matrices (PCNM) analysis of plot locations was fit to the response variables. Finally, the two models were combined into an overall regression model and variation partitioning was performed to determine the relatively importance of landscape structure variables, stand age, pure spatial dependence and shared variation on species density and biomass. PCNM analysis and multiple regressions were used to identify landscape structure and stand age variables related to response variables at different spatial scales (Bocard et al, 2004). First, we partitioned the spatial model for each response variable into several additive submodels, and run a variogram analysis of significant PCNM vectors to identify their scale and assign them to one of three groups: very board scale (distances of 8001 to 10500 m), broad scale (distances of 2001 to 8000 m), and local scale (distances of 0 to 2000 m). Then, we calculated predicted values of species density and biomass corresponding to each spatial submodel. Finally, a multiple regression model using stand age and landscape structure metrics was fit to the predicted response variables for each submodel (very broad, broad and local scale). 3. Results The land cover thematic map of the study area is shown in Figure 1. This landscape covers a total area of 37 242 ha; 94.3% is covered by forest in any of the four vegetation classes, and only 5.7% is covered by agriculture, urban areas and roads. The overall accuracy calculated for the map was 75.6%, and the Kappa index was 0.7. Figure 1: Location and land cover map of the study area obtained from a supervised classification. 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.
Page 1 and 2:
Landscapes Forest and Global Change
Page 3:
The contributions to this volume ha
Page 6 and 7:
Table of contents Foreword Preface
Page 8 and 9:
Fine-scale mapping of High Nature V
Page 10 and 11:
Characterization of a Maculinea alc
Page 12 and 13:
Urban tree inventory and socio-econ
Page 14 and 15:
xiii Foreword Twenty years ago, Dr.
Page 16 and 17:
Section 1 Scaling in landscape anal
Page 18 and 19:
V. Cortes et al. 2010. Environmenta
Page 20 and 21:
Page 22 and 23:
Page 24 and 25:
D. S. de Ron et al. 2010. Habitat s
Page 26 and 27:
Page 28 and 29:
Page 30 and 31:
B. Bożętka 2010. Recent relations
Page 32 and 33:
Page 34 and 35:
Page 36 and 37:
S.F. Chen et al. 2010. A physiotope
Page 38 and 39:
Page 40 and 41:
Page 42 and 43:
V.D. de Campos & S M. Carvalho 2010
Page 44 and 45:
Page 46 and 47:
Page 48 and 49:
N.S. Evseeva & Z.N. Kvasnikova 2010
Page 50 and 51:
N.S. Evseeva & Z.N. Kvasnikova 2010
Page 52 and 53:
S. Frank et al. 2010. A regionally
Page 54 and 55:
Page 56 and 57:
Page 58 and 59:
M. García et al. 2010. The effect
Page 60 and 61:
M. García et al. 2010. The effect
Page 62 and 63:
S. Gholami et al. 2010. Spatial pat
Page 64 and 65:
Page 66 and 67:
Page 68 and 69:
P. González-Moreno et al. 2010. Th
Page 70 and 71:
Page 72 and 73:
Page 74 and 75:
T. Höbinger et al. 2010. Impact of
Page 76 and 77:
Page 78 and 79:
Page 80 and 81:
P. Matos et al. 2010. Can lichen fu
Page 82 and 83:
Page 84 and 85:
Page 86 and 87:
E.S. Meier et al. 2010. Projections
Page 88 and 89:
E.S. Meier et al. 2010. Projections
Page 90 and 91:
H. Moutahir et al. 2010. Applicatio
Page 92 and 93:
H. Moutahir et al. 2010. Applicatio
Page 94 and 95:
C. Palaghianu 2010. The use of Voro
Page 96 and 97:
Page 98 and 99:
Page 100 and 101:
F. Peña-Cortés et al. 2010. Spati
Page 102 and 103:
Page 104 and 105:
Page 106 and 107:
F.M. Rabenilalana et al. 2010. Mult
Page 108 and 109:
Page 110 and 111:
Page 112 and 113:
A. Ruskule et al. 2010. Patterns of
Page 114 and 115:
Page 116 and 117:
Page 118 and 119:
E. Sayad 2010. Nitrogen retrancloca
Page 120 and 121:
E. Sayad 2010. Nitrogen retrancloca
Page 122 and 123:
G. Zhelezov 2010. Evaluation of the
Page 124 and 125:
Page 126 and 127:
Page 128 and 129:
Section 3 Disturbances in changing
Page 130 and 131:
A. Altamirano et al. 2010. Human-ca
Page 132 and 133:
A. Altamirano et al. 2010. Human-ca
Page 134 and 135:
T. Curt & J. Pausas 2010. Are chang
Page 136 and 137:
Page 138 and 139:
Page 140 and 141:
R.A Fleming et al. 2010. Forest man
Page 142 and 143:
R.A Fleming et al. 2010. Forest man
Page 144 and 145:
P.C. Goebel et al. 2010. How import
Page 146 and 147:
Page 148 and 149:
Page 150 and 151:
L.R. Iverson et al. 2010. Merger of
Page 152 and 153:
Page 154 and 155:
Page 156 and 157:
T.-C. Lin et al. 2010. Immediate ef
Page 158 and 159:
Page 160 and 161:
Page 162 and 163:
K. L. Martin & P.C. Goebel 2010. Im
Page 164 and 165:
Page 166 and 167:
Page 168 and 169:
G.M. Pastur et al. 2010. Indirect e
Page 170 and 171:
Page 172 and 173:
Page 174 and 175:
E.W Saragih et al. 2010. Effects of
Page 176 and 177:
Page 178 and 179:
Page 180 and 181:
L.R.P. Williamson et al. 2010. Anth
Page 182 and 183:
Page 184 and 185:
Page 186 and 187:
N. Zurbriggen et al. 2010. Modeling
Page 188 and 189:
Page 190 and 191:
Page 192 and 193:
Section 4 Biodiversity conservation
Page 194 and 195:
Akbarzadeh et al. 2010. Ecotourism
Page 196 and 197:
Akbarzadeh et al. 2010. Ecotourism
Page 198 and 199:
C. Carvalho-Santos 2010. Fine-scale
Page 200 and 201:
Page 202 and 203:
Page 204 and 205:
I. Catalano et al. 2010. Wood macro
Page 206 and 207:
Page 208 and 209:
Page 210 and 211:
R.A. Diaz-Varela et al. 2010. Exten
Page 212 and 213:
Page 214 and 215:
Page 216 and 217:
R.A. Diaz-Varela et al. 2010. Asses
Page 218 and 219:
Page 220 and 221:
Page 222 and 223:
P.A.E. Diogo & J. Aranha 2010. GIS
Page 224 and 225:
P.A.E. Diogo & J. Aranha 2010. GIS
Page 226 and 227:
V. Etemad & N. Avani 2010. Investig
Page 228 and 229:
Page 230 and 231:
Page 232 and 233:
A.E. Eycott et al. 2010. The impact
Page 234 and 235:
Page 236 and 237:
Page 238 and 239:
E. Fernández-Núñez et al. 2010.
Page 240 and 241:
Page 242 and 243:
Page 244 and 245:
N. Fracassi & D. Somma 2010. Partic
Page 246 and 247:
Page 248 and 249:
Page 250 and 251:
J. Hartter et al. 2010. Fortresses
Page 252 and 253:
Page 254 and 255:
Page 256 and 257:
M.B. Horta et al. 2010. Landscape S
Page 258 and 259:
Page 260 and 261:
Page 262 and 263:
J.O. López-Martínez et al. 2010.
Page 264 and 265:
Page 266 and 267:
Page 268 and 269:
Sara Marques et al. 2010. Impact of
Page 270 and 271:
Page 272 and 273:
Page 274 and 275:
M.G.C. Martins & J. Aranha 2010. El
Page 276 and 277:
M.G.C. Martins & J. Aranha 2010. El
Page 278 and 279:
J.-F. Mas et al. 2010. Modeling lan
Page 280 and 281:
Page 282 and 283:
Page 284 and 285:
R.S. Moro & T.K. Pereira 2010. Eval
Page 286 and 287:
Page 288 and 289:
Page 290 and 291:
R.S. Moro & C.H Rocha 2010. A metho
Page 292 and 293:
Page 294 and 295:
Page 296 and 297:
V. Núñez et al. 2010. Landscape i
Page 298 and 299:
Page 300 and 301:
Page 302 and 303:
S.G. Plexida & A.I. Sfougaris 2010.
Page 304 and 305:
Page 306 and 307:
Page 308 and 309:
A. Poljanec & A. Boncina 2010. Chan
Page 310 and 311:
Page 312 and 313:
Page 314 and 315:
M. Redon & S. Luque 2010. Tengmalm
Page 316 and 317:
Page 318 and 319:
Page 320 and 321:
M.C.C. Rodrigues et al. 2010. Contr
Page 322 and 323:
M.C. Silva et al. 2010. Using Busin
Page 324 and 325:
Page 326 and 327:
Page 328 and 329:
T.N. Terra & R.F dos Santos 2010. L
Page 330 and 331:
Page 332 and 333:
Page 334 and 335:
E. Tetetla-Rangel et al. 2010. Rela
Page 336 and 337:
Page 338 and 339:
Page 340 and 341:
M. Tsibulnikova 2010. Economic esti
Page 342 and 343:
Page 344 and 345:
Page 346 and 347:
M. Akbarzadeh & E. Kouhgardi 2010.
Page 348 and 349:
Page 350 and 351:
Page 352 and 353:
B. Baran-Zgłobicka & W. Zgłobicki
Page 354 and 355:
B. Baran-Zgłobicka & W. Zgłobicki
Page 356 and 357:
J. Beldade & T. Panagopoulos 2010.
Page 358 and 359:
Page 360 and 361:
Page 362 and 363:
S.M. Carvalho & A.R. de Freitas 201
Page 364 and 365:
Page 366 and 367:
Page 368 and 369:
R.A. Diaz-Varela et al. 2010. Quant
Page 370 and 371:
Page 372 and 373:
Page 374 and 375:
I. Duarte & F.C. Rego 2010. Land us
Page 376 and 377:
Page 378 and 379:
Page 380 and 381:
J.S.V. Filho & M.L. Leite 2010. Sim
Page 382 and 383:
Page 384 and 385:
Page 386 and 387:
F.J. Gómez et al. 2010. Land use c
Page 388 and 389:
Page 390 and 391:
Page 392 and 393:
M.L. Leite & J.S.V. Filho2010. Anal
Page 394 and 395:
M.L. Leite & J.S.V. Filho2010. Anal
Page 396 and 397:
M.L.Leite & J.S.V. Filho 2010. Iden
Page 398 and 399:
Page 400 and 401:
Page 402 and 403:
M. Ortega et al. 2010. Monitoring v
Page 404 and 405:
Page 406 and 407:
Page 408 and 409:
G. Puddu et al. 2010. Landscape tra
Page 410 and 411:
Page 412 and 413:
Page 414 and 415:
H.R. Ratsimba et al. 2010. Multi-sc
Page 416 and 417:
Page 418 and 419:
Page 420 and 421:
M.C. Rodrigues et al. 2010. Charact
Page 422 and 423:
M.C. Rodrigues et al. 2010. Charact
Page 424 and 425:
M.T.C. Rodrigues & V. Silva 2010. L
Page 426 and 427:
Page 428 and 429:
Page 430 and 431:
J. Schaefer-Santos & C. Lingnau 201
Page 432 and 433:
Page 434 and 435:
Page 436 and 437:
S.M. Scheffer & E. Schimanski 2010.
Page 438 and 439:
S.M. Scheffer & E. Schimanski 2010.
Page 440 and 441:
J. Superson et al. 2010. The defore
Page 442 and 443:
Page 444 and 445:
Page 446 and 447:
A.L. Teixido et al. 2010. Impacts o
Page 448 and 449:
Page 450 and 451:
Page 452 and 453:
H. Viana & J. Aranha 2010. Assessin
Page 454 and 455:
Page 456 and 457:
Page 458 and 459:
H. Viana & J. Aranha 2010. Mapping
Page 460 and 461:
Page 462 and 463:
Page 464 and 465:
Section 6 Tools of landscape assess
Page 466 and 467:
N. Avani et al. 2010. Investigation
Page 468 and 469:
Page 470 and 471:
Page 472 and 473:
J.C. Azevedo et al. 2010. Spatial d
Page 474 and 475:
Page 476 and 477:
Page 478 and 479:
T. Batista et al. 2010. The third d
Page 480 and 481:
Page 482 and 483:
Page 484 and 485:
V. Caboun 2010. New classification
Page 486 and 487:
Page 488 and 489:
Page 490 and 491:
A.M. Carvalho et al. 2010. Connecti
Page 492 and 493:
Page 494 and 495:
Page 496 and 497:
M. Deconchat et al. 2010. Identific
Page 498 and 499:
Page 500 and 501:
Page 502 and 503:
J. Gaspar et al. 2010. Visibility a
Page 504 and 505:
J. Gaspar et al. 2010. Visibility a
Page 506 and 507:
A.M. Geraldes 2010. Landscape runof
Page 508 and 509:
Page 510 and 511:
Page 512 and 513:
A.M. Geraldes & M.J. Boavida 2010.
Page 514 and 515:
Page 516 and 517:
Page 518 and 519:
K. Koschke et al. 2010. Using a mul
Page 520 and 521:
Page 522 and 523:
Page 524 and 525:
J.-F. Mas et al. 2010. Assessing
Page 526 and 527:
Page 528 and 529:
Page 530 and 531:
A. Matos et al. 2010. Economic valu
Page 532 and 533:
Page 534 and 535:
Page 536 and 537:
A. Migliozzi et al. 2010. Land-use
Page 538 and 539:
Page 540 and 541:
Page 542 and 543:
M.L Porto et al. 2010. Naturalness
Page 544 and 545:
M.L Porto et al. 2010. Naturalness
Page 546 and 547:
M. Rehor & V. Ondracek 2010. Applic
Page 548 and 549:
Page 550 and 551:
Page 552 and 553:
J. Russell et al. 2010. Developing
Page 554 and 555:
Page 556 and 557:
Page 558 and 559:
Section 7 Management and sustainabi
Page 560 and 561:
P. Angelstam & M. Elbakidze. 2010.
Page 562 and 563:
Page 564 and 565:
Page 566 and 567:
M. Castro et al. 2010. Relationship
Page 568 and 569:
Page 570 and 571:
Page 572 and 573:
M. Elbakidze et al. 2010. Does fore
Page 574 and 575:
Page 576 and 577:
Page 578 and 579:
F. Fonseca & T. de Figueiredo 2010.
Page 580 and 581:
Page 582 and 583:
Page 584 and 585:
A. Gil-Tena et al. 2010. Disentangl
Page 586 and 587:
Page 588 and 589:
Page 590 and 591:
M.B. Horta & E. Keizer 2010. Assess
Page 592 and 593:
Page 594 and 595:
Page 596 and 597:
E. Kouhgardi & M. Akbarzadeh 2010.
Page 598 and 599:
Page 600 and 601:
Page 602 and 603:
E. Kouhgardi et al. 2010. Values of
Page 604 and 605:
E. Kouhgardi et al. 2010. Values of
Page 606 and 607:
E. Schimanski 2010. The importance
Page 608 and 609:
Page 610 and 611:
Page 612 and 613: L.A.M. da Silva & E. Shimanki 2010.
Page 618 and 619: N. Stryamets et al. 2010. Role of n
Page 624 and 625: E. Volkova 2010. The regional analy
Page 630 and 631: I. Löfström et al. 2010. Biodiver
Page 632 and 633: I. Löfström et al. 2010. Biodiver
Page 634 and 635: A.C.R. de Oliveira & S.M. Carvalho
Page 640 and 641: I. Silva et al. 2010. Lisbon’s pu
Page 646 and 647: Section 9 Symposia
Page 648 and 649: Z.L. Urech & J.P. Sorg 2010. Taking
Page 654 and 655: Measures of landscape structure as
Page 656 and 657: E.R. Diaz-Varela et al. 2010. Multi
Page 664 and 665: J.L. Hernández-Stefanoni et al. 20
Page 666 and 667: J.L. Hernández-Stefanoni et al. 20
Page 668 and 669: E. Uuemaa et al. 2010. Spatial grad
Page 674 and 675: E. Penot 2010. Socio-economic diagn
Page 680 and 681: Network theory to conserve and reco
Page 682 and 683: S. Decout et al. 2010. Connectivity
Page 688 and 689: S. Joost et al. 2010. GEOME. Toward
Page 694 and 695: S.R. Freitas et al. 2010. The effec
Page 700 and 701: B. Terrones et al. 2010. Detecting
Page 706 and 707: M. Kolström et al. 2010. Is it pos
Page 712 and 713:
S. M. Carvalho-Ribeiro & T. Pinto-C
Page 714 and 715:
Page 716 and 717:
Page 718 and 719:
J.P. Nunes et al. 2010. Impacts of
Page 720 and 721:
Page 722 and 723:
Page 724 and 725:
Management and conservation of Medi
Page 726 and 727:
P.M. Fernandes et al. 2010. Testing
Page 728 and 729:
Page 730 and 731:
Page 732 and 733:
E. Andrieu et al. 2010. When forest
Page 734 and 735:
Page 736 and 737:
Page 738 and 739:
D. Geni et al. 2010. A framework fo
Page 740 and 741:
Page 742 and 743:
Page 744 and 745:
A. Ouin et al. 2010. Do wooded elem
Page 746 and 747:
Page 748 and 749:
Page 750 and 751:
C. Estreguil & G. Caudullo 2010. Ha
Page 752 and 753:
Page 754 and 755:
Page 756 and 757:
J.M. Rey Benayas 2010. Restoration
Page 758 and 759:
Page 760 and 761:
Page 762:
IUFRO Unit 8.01.02 Landscape Ecolog
show all

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

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?