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Efficiency of inventory plot patterns in quantitative analysis of vegetation: a case study of tropical woodland and dense forest in Benin
被引:12
|作者:
Salako, Valere K.
[1
]
Kakai, Romain L. Glele
[1
]
Assogbadjo, Achille E.
[1
]
Fandohan, Belarmain
[1
,2
]
Houinato, Marcel
[1
]
Palm, Rodolphe
[3
]
机构:
[1] Univ Abomey Calavi, Fac Agron Sci, Cotonou, Benin
[2] Chinese Acad Sci, Inst Geog & Nat Resources Res, United Nations Environm Programme, Int Ecosyst Management Partnership, Beijing 100101, Peoples R China
[3] Univ Liege, AgroBio Tech, SIMa, B-5030 Gembloux, Belgium
关键词:
efficiency;
forest inventory;
plot patterns;
structure;
tropical vegetation types;
SIZE;
D O I:
10.2989/20702620.2013.816232
中图分类号:
S7 [林业];
学科分类号:
0829 ;
0907 ;
摘要:
The main issue in forest inventory is the reliability of data collected, which depends on the shape and size of inventoried plots. There is also a need for harmonisation of inventoried plot patterns in West Africa. This study focused on the impact of plot patterns on the quantitative analysis of two vegetation types of West Africa based on case studies from Benin. Twenty and fifteen plots of 1 ha each were demarcated in dense forest and woodland, respectively. Each 1 ha plot was divided into 100 quadrats of 100 m(2) each and diameter at breast height (dbh) of trees was recorded in each quadrat. The required time to measuring trees diameter in each 1 ha plot was also recorded to compute the mean inventory effort. From the 100 quadrats in each 1 ha plot, 14 subplots of different shapes and sizes were considered by grouping together adjacent quadrats. The basal area of each subplot was computed and the relationship between estimation bias of the basal area and the size of subplots was modeled using Smith's Law (Smith 1938). The mean absolute error of the shape parameter c of Weibull distribution was computed for each of the subplot shape, size and direction. The direction and shape of subplots did not influence significantly (P > 0.05) the precision of the quantitative analysis of vegetation. However, square subplots were suitable in practice. On the contrary, plot size was significantly (P < 0.05) and inversely correlated to estimation efficiency. The optimal plot size for quantitative analysis of vegetation was 1 800 and 2 000 m2 with an inventory effort of 0.51 and 0.85 man-days per subplot in woodland and dense forest, respectively. It is concluded that use of standard sample sizes will help to harmonise a forestry database and to carry out comparisons at regional level.
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页码:137 / 143
页数:7
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