Title
Can Airborne Laser Scanning (ALS) and Forest Estimates Derived from Satellite Images Be Used to Predict Abundance and Species Richness of Birds and Beetles in Boreal Forest?
Abstract
In managed landscapes, conservation planning requires effective methods to identify high-biodiversity areas. The objective of this study was to evaluate the potential of airborne laser scanning (ALS) and forest estimates derived from satellite images extracted at two spatial scales for predicting the stand-scale abundance and species richness of birds and beetles in a managed boreal forest landscape. Multiple regression models based on forest data from a 50-m radius (i.e., corresponding to a homogenous forest stand) had better explanatory power than those based on a 200-m radius (i.e., including also parts of adjacent stands). Bird abundance and species richness were best explained by the ALS variables "maximum vegetation height" and "vegetation cover between 0.5 and 3 m" (both positive). Flying beetle abundance and species richness, as well as epigaeic (i.e., ground-living) beetle richness were best explained by a model including the ALS variable "maximum vegetation height" (positive) and the satellite-derived variable "proportion of pine" (negative). Epigaeic beetle abundance was best explained by "maximum vegetation height" at 50 m (positive) and "stem volume" at 200 m (positive). Our results show that forest estimates derived from satellite images and ALS data provide complementary information for explaining forest biodiversity patterns. We conclude that these types of remote sensing data may provide an efficient tool for conservation planning in managed boreal landscapes.
Year
DOI
Venue
2015
10.3390/rs70404233
REMOTE SENSING
Keywords
Field
DocType
biodiversity hot spot,boreal forest,lidar,knn
Ecology,Physical geography,Vegetation,Satellite,Species richness,Biodiversity hotspot,Conservation planning,Remote sensing,Taiga,Lidar,Geology,Linear regression
Journal
Volume
Issue
Citations 
7
4
2
PageRank 
References 
Authors
0.40
4
4
Name
Order
Citations
PageRank
eva lindberg1264.41
jeanmichel roberge220.40
t johansson320.40
joakim hjalten420.40