Lidar-derived variables as a proxy for fungal species richness and composition in temperate Northern Europe

Thers, Henrik; Brunbjerg, Ane Kirstine; Læssøe, Thomas; Ejrnæs, Rasmus; Bøcher, Peder Klith; Svenning, Jens‐Christian

doi:10.1016/j.rse.2017.08.011

Cited by 25 publications

(42 citation statements)

References 59 publications

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“…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. However, in our study the explanatory power obtained for all species groups corresponds well to, or is even higher than, results from earlier studies relating LIDAR measures to species richness of fungi, lichens, plants, and bryophytes (Camathias et al 2013, Moeslund et al 2013a, Thers et al 2017, Bartels et al 2018. This suggests that LIDAR is not only suitable for management and planning of diversity in forests, but is probably more broadly applicable and likely to be a valuable support tool for nature management and planning in open landscapes as well.…”

Section: The Ability Of Lidar To Explain Local Species Richnesssupporting

confidence: 83%

“…, Thers et al. ). Instead of vegetation‐structure measures, other studies have used terrain measures derived from LIDAR‐based digital terrain models (DTM) such as aspect, elevation above sea level, slope, topographic wetness (Moeslund et al.…”

Section: Introductionmentioning

confidence: 99%

“…Most studies using these vegetation‐structure measures were restricted to forests (but see Thers et al. ) and have shown that local species richness can be modeled with explanatory power up to 66% for plants and up to 82% for fungi (Lopatin et al. , Peura et al.…”

Section: Introductionmentioning

confidence: 99%

“…The potential of LIDAR-based metrics for investigating and predicting species diversity has already been recognized for local-to-regional scale studies of various species groups (Vehmas et al 2009, Lopatin et al 2016, Peura et al 2016, Thers et al 2017, Mao et al 2018. Such studies typically used LIDAR-based indicators of general vegetation structure, such as vegetation height, variance of point height in individual height layers (Froidevaux et al 2016), and the count (or density) of points in various height layers (Vehmas et al 2009, Mao et al 2018.…”

Section: Introductionmentioning

confidence: 99%

“…Such studies typically used LIDAR-based indicators of general vegetation structure, such as vegetation height, variance of point height in individual height layers (Froidevaux et al 2016), and the count (or density) of points in various height layers (Vehmas et al 2009, Mao et al 2018. Most studies using these vegetation-structure measures were restricted to forests (but see Thers et al 2017) and have shown that local species richness can be modeled with explanatory power up to 66% for plants and up to 82% for fungi (Lopatin et al 2016, Peura et al 2016, Thers et al 2017. Instead of vegetation-structure measures, other studies have used terrain measures derived from LIDAR-based digital terrain models (DTM) such as aspect, elevation above sea level, slope, topographic wetness (Moeslund et al 2013a, Mao et al 2018, or depth-to-water indices (Bartels et al 2018).…”

Section: Introductionmentioning

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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Section: The Ability Of Lidar To Explain Local Species Richnesssupporting

confidence: 83%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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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Scrub encroachment promotes biodiversity in temperate European wetlands under eutrophic conditions

Brunbjerg

Fløjgaard

Frøslev

et al. 2022

Ecology and Evolution

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Wetlands are important habitats, often threatened by drainage, eutrophication, and suppression of grazing. In many countries, considerable resources are spent combatting scrub encroachment. Here, we hypothesize that encroachment may benefit biodiversity—especially under eutrophic conditions where asymmetric competition among plants compromises conservation targets. We studied the effects of scrub cover, nutrient levels, and soil moisture on the richness of vascular plants, bryophytes, soil fungi, and microbes in open and overgrown wetlands. We also tested the effect of encroachment, eutrophication, and soil moisture on indicators of conservation value (red‐listed species, indicator species, and uniqueness). Plant and bryophyte species richness peaked at low soil fertility, whereas soil fertility promoted soil microbes. Soil fungi responded negatively to increasing soil moisture. Lidar‐derived variables reflecting the degree of scrub cover had predominantly positive effects on species richness measures. Conservation value indicators had a negative relationship to soil fertility and a positive to encroachment. For plant indicator species, the negative effect of high nutrient levels was offset by encroachment, supporting our hypothesis of competitive release under shade. The positive effect of soil moisture on indicator species was strong in open habitats only. Nutrient‐poor mires and meadows host many rare species and require conservation management by grazing and natural hydrology. On former agricultural lands, where restoration of infertile conditions is unfeasible, we recommend rewilding with opportunities for encroachment toward semi‐open willow scrub and swamp forest, with the prospect of high species richness in bryophytes, fungi, and soil microbes and competitive release in the herb layer.

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Linking Foliar Traits to Belowground Processes

Madritch

Cavender‐Bares

Hobbie

et al. 2020

Remote Sensing of Plant Biodiversity

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Above- and belowground systems are linked via plant chemistry. In forested systems, leaf litter chemistry and quality mirror that of green foliage and have important afterlife effects. In systems where belowground inputs dominate, such as grasslands, or in ecosystems where aboveground biomass is frequently removed by burning or harvesting, foliar traits may provide important information regarding belowground inputs via exudates and fine-root turnover. Many, if not most, of the plant traits that drive variation in belowground processes are also measurable via remote sensing technologies. The ability of remote sensing techniques to measure fine-scale biodiversity and plant chemistry over large spatial scales can help researchers address ecological questions that were previously prohibitively expensive to address. Key to these potential advances is the idea that remotely sensed vegetation spectra and plant chemistry can provide detailed information about the function of belowground processes beyond what traditional field sampling can provide.

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Lidar-derived variables as a proxy for fungal species richness and composition in temperate Northern Europe

Cited by 25 publications

References 59 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

Scrub encroachment promotes biodiversity in temperate European wetlands under eutrophic conditions

Linking Foliar Traits to Belowground Processes

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