Home About Browse Search

Forest fragmentation assessment using field-based sampling data from forest inventories

Ramezani, Habib and Ramezani, Alireza (2021). Forest fragmentation assessment using field-based sampling data from forest inventories. Scandinavian Journal of Forest Research. 36 , 289-296
[Research article]

[img] PDF


Forest fragmentation has a relevant impact on biodiversity. An interesting alternative to estimate these indices is to use sampling data. This study aims to estimate aggregation index (AI) and the degree of clumping of forested landscape based on AI. The assessment was conducted using different point distances, inventory regions and cardinal directions. For this purpose, a dataset from one five-year periods (2007-2011) of the Swedish National Forest Inventory (NFI) was used. The estimation of AI from field-based inventory can give us a general picture of the current status of forest landscape. The results also show that the estimated AI is a distance dependent function. The corresponding estimated variance of the index is smaller for longer distances. The obtained results indicate that the estimated variance depends on both sample size and pair point distances. Estimated AI showed different values in different cardinal directions. To compare two regions or a given region over time, a given point distance should be used. The main advantage of the applied procedure is that a range of AI values can be produced rather than a single number. Furthermore, in field-based inventory, the obtained results are more reliable, because one works implicitly with a single forest definition only.

Authors/Creators:Ramezani, Habib and Ramezani, Alireza
Title:Forest fragmentation assessment using field-based sampling data from forest inventories
Series Name/Journal:Scandinavian Journal of Forest Research
Year of publishing :2021
Page range:289-296
Number of Pages:8
Publication Type:Research article
Article category:Scientific peer reviewed
Version:Published version
Copyright:Creative Commons: Attribution-Noncommercial-No Derivative Works 4.0
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Forest Science
Keywords:NFI, sampling methods, forest landscape, environmental monitoring
Permanent URL:
Additional ID:
Type of IDID
Web of Science (WoS)000635832300001
ID Code:24798
Faculty:S - Faculty of Forest Sciences
Department:(S) > Dept. of Forest Resource Management
(NL, NJ) > Dept. of Forest Resource Management
Deposited By: SLUpub Connector
Deposited On:05 Jul 2021 08:45
Metadata Last Modified:05 Jul 2021 08:51

Repository Staff Only: item control page


Downloads per year (since September 2012)

View more statistics