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[en]+[zh]Study on Forest Landscape Restoration - ITTO

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6 Analyzing landscape pattern at regi<strong>on</strong> level 203<br />

had be<str<strong>on</strong>g>en</str<strong>on</strong>g> kept stable in edge d<str<strong>on</strong>g>en</str<strong>on</strong>g>sity, patch shapes of Degraded Primary <strong>Forest</strong>,<br />

Sec<strong>on</strong>dary <strong>Forest</strong>, Degraded <strong>Forest</strong> Land, Rubber Plantati<strong>on</strong> and Resid<str<strong>on</strong>g>en</str<strong>on</strong>g>tial<br />

Quarters Land became more and more irregular, and other types had<br />

become more squared during 1999 to 2008.<br />

6. 3. 3 Predicti<strong>on</strong> of forest landscape dynamics<br />

Understanding the forest landscape dynamics is a major factor for successful<br />

implem<str<strong>on</strong>g>en</str<strong>on</strong>g>tati<strong>on</strong> of FLR initiative since it is a process that will take at least 10<br />

years, oft<str<strong>on</strong>g>en</str<strong>on</strong>g> much l<strong>on</strong>ger, facing major technical, ec<strong>on</strong>omic, social, cultural<br />

and instituti<strong>on</strong>al chall<str<strong>on</strong>g>en</str<strong>on</strong>g>ges. Using Markov models, transiti<strong>on</strong> probability matrix<br />

am<strong>on</strong>g differ<str<strong>on</strong>g>en</str<strong>on</strong>g>t landscape elem<str<strong>on</strong>g>en</str<strong>on</strong>g>t types from 1999 to 2008 (see Table<br />

6. 7) was c<strong>on</strong>structed to predict and analyze the forest landscape dynamics of<br />

Lingshui Li Aut<strong>on</strong>omous County.<br />

Table 6. 7<br />

<strong>Landscape</strong> class transiti<strong>on</strong> area of Lingshui<br />

Li Aut<strong>on</strong>omous County form 1999 to 2008<br />

2008<br />

1999 -------------------------<br />

ff ~ ~ ~ & ~ ~ ~ ~ ~ ~ II OC<br />

PF 4.74<br />

DPF<br />

SF<br />

DFL<br />

RP<br />

TaV<br />

CeP<br />

OP<br />

OFL<br />

RQL<br />

6. 29 O. 85 O. 09 0.21 0.03<br />

21. 95 0.93 0.31 0.18 0.90<br />

O. 16 0.23 0.03 0.01 0.97<br />

O. 04 O. 66 O. 50 O. 11<br />

0.01 O. 17 O. 08 O. 04<br />

0.42 5.50 0.21 0.65 0.04 0.07 1. 11 O. 61 O. 11<br />

0.02 0.04 2.60 0.02 0.45 0.01 0.72 0.71 1. 75 0.23<br />

0.01 0.05 0.02 0.23 O. 12<br />

QU QTI Q~ Q~ Q~ Q04 QM Q© Q~ QW<br />

QID Q~ Q~ Qm QOO Q~ Q~ Q01<br />

QOO QID Q~ Q01 Q® 1.~ Q® QW Q04<br />

GP 0.00 0.14 0.15 0.10 O. 03 O. 50 O. 72 O. 02 1. 66<br />

1999<br />

4.74<br />

7.48<br />

25.59<br />

1. 71<br />

8.72<br />

6.56<br />

0.43<br />

3.88<br />

LlO<br />

AL 0.32 0.81 2.32 0.08 1. 91 0.05 0.86 3.22 17.83 1. 47 28.88<br />

OL 0.07 0.17 0.20 0.20 0.59 0.01 0.12 0.43 1.16 3.49 6.44<br />

2008 4.74 6.29 22.80 2.17 7.66 6.78 0.42 6.66 0.16 3.80 8.00 24.54 5.96 100.00<br />

Note:PF - Primary <strong>Forest</strong>, DPF - Degraded Primary <strong>Forest</strong>, SF - Sec<strong>on</strong>dary <strong>Forest</strong>,DFL - Degraded<strong>Forest</strong> Land, RP<br />

- Rubber Plantati<strong>on</strong>, Ta V - Trees around Villages, CeP Casuarina equisetifolia Plantati<strong>on</strong>, OP - Other Plantati<strong>on</strong>, OFL<br />

- Other <strong>Forest</strong> Land, RQL - Resid<str<strong>on</strong>g>en</str<strong>on</strong>g>tial Quarters Land, GP - Gard<str<strong>on</strong>g>en</str<strong>on</strong>g> Plots, AL - Agricultural Land, OL - Other<br />

Land.<br />

The results (see Table 6. 8 and Figure 6. 2) showed that forest and other<br />

natural landscape would reduce gradually while semi-natural landscapes such<br />

as agricultural land and "human-induced landscape like resid<str<strong>on</strong>g>en</str<strong>on</strong>g>tial quarters<br />

2.81

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