Disentangling the effects of climate, topography, soil and vegetation on stand-scale species richness in temperate forests

Zellweger, Florian; Braunisch, Veronika; Morsdorf, Felix; Baltensweiler, Andri; Abegg, Meinrad; Roth, Tobias; Bugmann, Harald; Bollmann, Kurt

doi:10.1016/j.foreco.2015.04.008

Cited by 60 publications

(51 citation statements)

References 201 publications

(187 reference statements)

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“…, Zellweger et al. ). In particular, the local diversity in these groups strongly depend on soil characteristics (Ejrnæs and Bruun , Ilomets et al.…”

Section: Discussionmentioning

confidence: 99%

“…So far, only a few studies have studied the extent to which LIDAR measures can predict diversity across multiple species groups, and these have included only one habitat type (see, for example, Zellweger et al. , ). Intuitively, one could expect LIDAR to predict local diversity in forests better than in open landscapes since LIDAR represents the more complex, three‐dimensional, vegetation structure in forests particularly well.…”

Section: Discussionmentioning

confidence: 99%

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Light detection and ranging explains diversity of plants, fungi, lichens, and bryophytes across multiple habitats and large geographic extent

Moeslund

Zlinszky

Ejrnæs

et al. 2019

Ecological Applications

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Effective planning and nature management require spatially accurate and comprehensive measures of the factors important for biodiversity. Light detection and ranging (LIDAR) can provide exactly this, and is therefore a promising technology to support future nature management and related applications. However, until now studies evaluating the potential of LIDAR for this field have been highly limited in scope. Here, we assess the potential of LIDAR to estimate the local diversity of four species groups in multiple habitat types, from open grasslands and meadows over shrubland to forests and across a large area (~43,000 km2), providing a crucial step toward enabling the application of LIDAR in practice, planning, and policy‐making. We assessed the relationships between the species richness of macrofungi, lichens, bryophytes, and plants, respectively, and 25 LIDAR‐based measures related to potential abiotic and biotic diversity drivers. We used negative binomial generalized linear modeling to construct 19 different candidate models for each species group, and leave‐one‐region‐out cross validation to select the best models. These best models explained 49%, 31%, 32%, and 28% of the variation in species richness (R 2) for macrofungi, lichens, bryophytes, and plants, respectively. Three LIDAR measures, terrain slope, shrub layer height and variation in local heat load, were important and positively related to the richness in three of the four species groups. For at least one of the species groups, four other LIDAR measures, shrub layer density, medium‐tree layer density, and variations in point amplitude and in relative biomass, were among the three most important. Generally, LIDAR measures exhibited strong associations to the biotic environment, and to some abiotic factors, but were poor measures of spatial landscape and temporal habitat continuity. In conclusion, we showed how well LIDAR alone can predict the local biodiversity across habitats. We also showed that several LIDAR measures are highly correlated to important biodiversity drivers, which are notoriously hard to measure in the field. This opens up hitherto unseen possibilities for using LIDAR for cost‐effective monitoring and management of local biodiversity across species groups and habitat types even over large areas.

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“…, Zellweger et al. ). In particular, the local diversity in these groups strongly depend on soil characteristics (Ejrnæs and Bruun , Ilomets et al.…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Light detection and ranging explains diversity of plants, fungi, lichens, and bryophytes across multiple habitats and large geographic extent

Moeslund

Zlinszky

Ejrnæs

et al. 2019

Ecological Applications

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“…In addition to soil factors, the distribution of plant communities might be related to the specific geographical location providing unique habitats (Wassen, Peeters, and Venterink 2002;Dwirek, Kauffman, and Baham 2006;Mellado and Zamora 2015;Oliveira, Torezan, and Cunha 2015;Zellweger et al 2015;Whitworth et al 2016). The plant communities in the study area were divided into seven types, which had substantial differences in their growth requirements.…”

Section: Relationship Between Vegetation and Soil Factorsmentioning

confidence: 99%

Distribution patterns of plant communities and their associations with environmental soil factors on the eastern shore of Lake Taihu, China

Sun

Zhao

et al. 2017

Ecosyst Health Sustain

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Introduction: Plant communities and soil factors might interact with each other in different temporal and spatial scales, which can influence the patterns and processes of the wetland ecosystem. To get a better understanding of the distribution of plants in wetlands and analyze their associations with environmental soil factors, the structure and types of plant communities in the eastern shore area of Lake Taihu were analyzed by two-way indicator species analysis and canonical correspondence analysis (CCA) ordination. The spatial distribution patterns of vegetation and the main factors affecting the distributions were investigated. Outcomes: Sixty-six sampling sites were selected to obtain vegetation species and soil environmental factor data. Results showed that 22 species from the 66 sites could be divided into seven communities: I: Arundo donax; II: A. donax + Phragmites australis; III: Zizania latifolia + Typha orientalis; IV: P. australis + Alternanthera philoxeroides + Polygonum hydropiper; V: P. australis; VI: P. australis + Humulus scandens; and VII: Erigeron acer + Ipomoea batatas + Rumex acetosa. Plant species and soil factors in the CCA analysis showed that I. batatas, E. acer, Chenopodium album, Polygonum lapathifolium, and Acalypha australis were mainly affected by pH, whereas Echinochloa crus-galli, Setaria viridis, and H. scandens were mainly affected by soil total phosphorus. Mentha canadensis and A. donax were mainly affected by soil conductivity, A. philoxeroides was mainly affected by soil organic matter and, Z. latifolia, Metaplexis japonica and P. hydropiper were mainly affected by available phosphorus. Conclusion:These results indicated that different plants adapted to different soil environmental factors and provided basic information on the diversity of Lake Taihu wetland vegetation.

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“…Our method involves several steps: (1) the derivation of a CHM from stereo aerial imagery; (2) the quantification of canopy cover and height for pre-stratification; (3) the mapping of forest gaps and their changes; (4) the detection of gaps in specific locations (i.e., on forest roads); (5) the evaluation of the mapping accuracy; and finally (6) the identification of the main sources of error. In addition to the main aim, the mapping of forest gaps, the intermediate processing steps deliver other important forest structure parameters such as canopy cover and forest height diversity that are frequently required as predictor variables for species-habitat studies in forest ecosystems [36,37].…”

Section: Introductionmentioning

confidence: 99%

Automated Detection of Forest Gaps in Spruce Dominated Stands Using Canopy Height Models Derived from Stereo Aerial Imagery

et al. 2016

Self Cite

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Forest gaps are important structural elements in forest ecology to which various conservation-relevant, photophilic species are associated. To automatically map forest gaps and detect their changes over time, we developed a method based on Digital Surface Models (DSM) derived from stereoscopic aerial imagery and a LiDAR-based Digital Elevation Model (LiDAR DEM). Gaps were detected and delineated in relation to height and cover of the surrounding forest comparing data from two public flight campaigns (2009 and 2012) in a 1023-ha model region in the Northern Black Forest, Southwest Germany. The method was evaluated using an independent validation dataset obtained by visual stereo-interpretation. Gaps were automatically detected with an overall accuracy of 0.90 (2009) and 0.82 (2012). However, a very high users' accuracy of more than 0.95 (both years) was counterbalanced by a producer's accuracy of 0.84 (2009) and 0.73 (2012) as some gaps were not automatically detected. Accuracy was mainly dependent on the shadow occurrence and height of the surrounding forest with producer's accuracies dropping to 0.70 (2009) and 0.52 (2012) in high stands (>8 m tree height). As one important step in the workflow, the class of open forest, an important feature for many forest species, was delineated with a very good overall accuracy of 0.92 (both years) with uncertainties occurring mostly in areas with intermediate canopy cover. Presence of complete or partial shadow and geometric limitations of stereo image matching were identified as the main sources of errors in the method performance, suggesting that images with a higher overlap and resolution and ameliorated image-matching algorithms provide the greatest potential for improvement.

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Disentangling the effects of climate, topography, soil and vegetation on stand-scale species richness in temperate forests

Cited by 60 publications

References 201 publications

Light detection and ranging explains diversity of plants, fungi, lichens, and bryophytes across multiple habitats and large geographic extent

Light detection and ranging explains diversity of plants, fungi, lichens, and bryophytes across multiple habitats and large geographic extent

Distribution patterns of plant communities and their associations with environmental soil factors on the eastern shore of Lake Taihu, China

Automated Detection of Forest Gaps in Spruce Dominated Stands Using Canopy Height Models Derived from Stereo Aerial Imagery

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