Literature DB >> 21563587

Spinning a laser web: predicting spider distributions using LiDAR.

K T Vierling1, C Bässler, R Brandl, L A Vierling, I Weiss, J Müller.   

Abstract

LiDAR remote sensing has been used to examine relationships between vertebrate diversity and environmental characteristics, but its application to invertebrates has been limited. Our objectives were to determine whether LiDAR-derived variables could be used to accurately describe single-species distributions and community characteristics of spiders in remote forested and mountainous terrain. We collected over 5300 spiders across multiple transects in the Bavarian National Park (Germany) using pitfall traps. We examined spider community characteristics (species richness, the Shannon index, the Simpson index, community composition, mean body size, and abundance) and single-species distribution and abundance with LiDAR variables and ground-based measurements. We used the R2 and partial R2 provided by variance partitioning to evaluate the predictive power of LiDAR-derived variables compared to ground measurements for each of the community characteristics. The total adjusted R2 for species richness, the Shannon index, community species composition, and body size had a range of 25-57%. LiDAR variables and ground measurements both contributed >80% to the total predictive power. For species composition, the explained variance was approximately 32%, which was significantly greater than expected by chance. The predictive power of LiDAR-derived variables was comparable or superior to that of the ground-based variables for examinations of single-species distributions, and it explained up to 55% of the variance. The predictability of species distributions was higher for species that had strong associations with shade in open-forest habitats, and this niche position has been well documented across the European continent for spider species. The similar statistical performance between LiDAR and ground-based measures at our field sites indicated that deriving spider community and species distribution information using LiDAR data can provide not only high predictive power at relatively low cost, but may also allow unprecedented mapping of community- and species-level spider information at scales ranging from stands to landscapes. Therefore, LiDAR is a viable tool to assist species-specific conservation as well as broader biodiversity planning efforts not only for a growing list of vertebrates, but for invertebrates as well.

Mesh:

Year:  2011        PMID: 21563587     DOI: 10.1890/09-2155.1

Source DB:  PubMed          Journal:  Ecol Appl        ISSN: 1051-0761            Impact factor:   4.657


  7 in total

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2.  Riverine Landscape Patch Heterogeneity Drives Riparian Ant Assemblages in the Scioto River Basin, USA.

Authors:  Paradzayi Tagwireyi; S Mažeika P Sullivan
Journal:  PLoS One       Date:  2015-04-20       Impact factor: 3.240

3.  Rapid, High-Resolution Forest Structure and Terrain Mapping over Large Areas using Single Photon Lidar.

Authors:  Anu Swatantran; Hao Tang; Terence Barrett; Phil DeCola; Ralph Dubayah
Journal:  Sci Rep       Date:  2016-06-22       Impact factor: 4.379

4.  Remotely sensed forest understory density and nest predator occurrence interact to predict suitable breeding habitat and the occurrence of a resident boreal bird species.

Authors:  Julian Klein; Paul J Haverkamp; Eva Lindberg; Michael Griesser; Sönke Eggers
Journal:  Ecol Evol       Date:  2020-02-05       Impact factor: 2.912

5.  Using satellite and airborne LiDAR to model woodpecker habitat occupancy at the landscape scale.

Authors:  Lee A Vierling; Kerri T Vierling; Patrick Adam; Andrew T Hudak
Journal:  PLoS One       Date:  2013-12-06       Impact factor: 3.240

6.  Modelling patterns of pollinator species richness and diversity using satellite image texture.

Authors:  Sylvia Hofmann; Jeroen Everaars; Oliver Schweiger; Mark Frenzel; Lutz Bannehr; Anna F Cord
Journal:  PLoS One       Date:  2017-10-03       Impact factor: 3.240

7.  Radar vision in the mapping of forest biodiversity from space.

Authors:  Soyeon Bae; Shaun R Levick; Lea Heidrich; Paul Magdon; Benjamin F Leutner; Stephan Wöllauer; Alla Serebryanyk; Thomas Nauss; Peter Krzystek; Martin M Gossner; Peter Schall; Christoph Heibl; Claus Bässler; Inken Doerfler; Ernst-Detlef Schulze; Franz-Sebastian Krah; Heike Culmsee; Kirsten Jung; Marco Heurich; Markus Fischer; Sebastian Seibold; Simon Thorn; Tobias Gerlach; Torsten Hothorn; Wolfgang W Weisser; Jörg Müller
Journal:  Nat Commun       Date:  2019-10-18       Impact factor: 14.919

  7 in total

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